Bayesian Statistical Modeling in Action for Estimation and Forecasting in Low- and Middle-income Countries: The Case of the Family Planning Estimation Tool

The Family Planning Estimation Tool (FPET) is used in low- and middle-income countries to produce estimates and short-term forecasts of family planning indicators, such as modern contraceptive use and unmet need for contraceptives. Estimates are obtained via a Bayesian statistical model that is fitted to country-specific data from surveys and service statistics data. The model has evolved over the last decade based on user inputs.In this paper we summarize the main features of the statistical model used in FPET and introduce recent updates related to capturing contraceptive transitions, fitting to survey data that may be error prone, and the use of service statistics data. We assess model performance through a validation exercise and find that FPET is reasonably well calibrated.We use our experience with FPET to briefly discuss lessons learned and open challenges related to the broader field of statistical modeling for monitoring of demographic and global health indicators.

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Journal
Statistics and Public Policy
Published
2026-09-21
DOI
https://doi.org/10.1080/2330443x.2026.2735367
Primary Topic
Statistical Methods and Bayesian Inference
Type
article
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article

Bayesian Statistical Modeling in Action for Estimation and Forecasting in Low- and Middle-income Countries: The Case of the Family Planning Estimation Tool

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Statistics and Public Policy
Statistical Methods and Bayesian Inference
article

Bayesian Statistical Modeling in Action for Estimation and Forecasting in Low- and Middle-income Countries: The Case of the Family Planning Estimation Tool

Emily Sonneveldt, Brighton Muzavazi, Priya Emmart, Zenon Mujani, Rogers Kagimu, S.J. Mooney, Herbert Susmann, Khan Muhammad, Kristin Bietsch, Evan Ray, Rebecca Rosenberg, Niamh Cahill, A.A. Jayachandran, Leontine Alkema, John Stover
article en

Abstract

The Family Planning Estimation Tool (FPET) is used in low- and middle-income countries to produce estimates and short-term forecasts of family planning indicators, such as modern contraceptive use and unmet need for contraceptives. Estimates are obtained via a Bayesian statistical model that is fitted to country-specific data from surveys and service statistics data. The model has evolved over the last decade based on user inputs.In this paper we summarize the main features of the statistical model used in FPET and introduce recent updates related to capturing contraceptive transitions, fitting to survey data that may be error prone, and the use of service statistics data. We assess model performance through a validation exercise and find that FPET is reasonably well calibrated.We use our experience with FPET to briefly discuss lessons learned and open challenges related to the broader field of statistical modeling for monitoring of demographic and global health indicators.

Statistics and Public Policy
Tulane University (US), National University of Ireland, Maynooth (IE), University of Massachusetts Amherst (US), Ministry of Health (OM), Avenir Health (US), College Track (US)
No poverty
Openalex Percentile: Top 8%
Statistical Methods and Bayesian Inference
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